The authors propose a new model parameter compensation algorithm based on parallel model combination (PMC). If differs from PMC in that the amount of adaption for the parameters is varied depending on the states and m...
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The authors propose a new model parameter compensation algorithm based on parallel model combination (PMC). If differs from PMC in that the amount of adaption for the parameters is varied depending on the states and mixture components of continuous density HMM. A state-dependent association factor which determines the adaption is employed and obtained by an EM algorithm.
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